TPC-H Skew Q3 — Shipping Priority

TPC-H Skew benchmark · all TPC-H Skew queries

Top 10 unshipped orders with highest value

Representative SQL

Rendered for DataFusion with default parameters.

SELECT
  l_orderkey,
  SUM(l_extendedprice * (
    1 - l_discount
  )) AS revenue,
  o_orderdate,
  o_shippriority
FROM customer, orders, lineitem
WHERE
  c_mktsegment = 'BUILDING'
  AND c_custkey = o_custkey
  AND l_orderkey = o_orderkey
  AND o_orderdate < CAST('1995-03-15' AS DATE)
  AND l_shipdate > CAST('1995-03-15' AS DATE)
GROUP BY
  l_orderkey,
  o_orderdate,
  o_shippriority
ORDER BY
  revenue DESC,
  o_orderdate
LIMIT 10

Representative DataFrame

Expression family (Polars, PySpark, DataFusion), default parameters.

def q3_expression_impl(ctx: DataFrameContext) -> Any:
    customer = ctx.get_table("customer")
    orders = ctx.get_table("orders")
    lineitem = ctx.get_table("lineitem")
    col = ctx.col
    lit = ctx.lit

    params = get_tpch_parameters(3)
    segment = params["segment"]
    order_date = params["order_date"]

    return (
        customer.filter(col("c_mktsegment") == lit(segment))
        .join(orders, left_on="c_custkey", right_on="o_custkey")
        .filter(col("o_orderdate") < lit(order_date))
        .join(lineitem, left_on="o_orderkey", right_on="l_orderkey")
        .filter(col("l_shipdate") > lit(order_date))
        .group_by("o_orderkey", "o_orderdate", "o_shippriority")
        .agg((col("l_extendedprice") * (lit(1) - col("l_discount"))).sum().alias("revenue"))
        .select("o_orderkey", "revenue", "o_orderdate", "o_shippriority")
        .sort(["revenue", "o_orderdate"], descending=[True, False])
        .limit(10)
    )

Get the exact query for your run

The blocks above are representative. To get the precise statement a specific platform runs at a specific scale, substitute your own values:

from benchbox import TPCHSkew

bench = TPCHSkew(scale_factor=0.01)            # your scale factor
queries = bench.get_queries(dialect="datafusion")   # your platform's dialect; drop dialect= for native SQL
print(queries['3'])

Parameter substitution for this benchmark is seed-driven; pass a seed for a specific stream’s parameters:

print(bench.get_query(3, scale_factor=0.01, seed=42, dialect="datafusion"))

For the DataFrame form:

from benchbox.core.query_catalog import get_dataframe_render

print(get_dataframe_render('tpch_skew', '3', family="expression").source)  # or family="pandas"

Source

Query text: benchbox/_binaries/tpc-h/templates/queries/3.sql